Manhattan WMOS Engineer
ShyftLabs
Support Manhattan WMOS implementations and operations as a WMS Engineer at ShyftLabs. ShyftLabs builds data products and digital solutions for Fortune 500 companies.
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Pearson VUE консалтинг, денсаулық сақтау және логистика сияқты түрлі салалардағы ұйымдарға компьютер арқылы тестілеу және біліктілікті растау қызметтерін ұсынады. Оның платформасы емтиханды жоспарлау, үміткерлерге арналған ресурстар және тестілеу жағдайларын бейімдеу құралдарымен бірге жауапкершілігі жоғары сертификаттау мен кәсіби емтихандарды қолдайды. Pearson VUE емтихан иелеріне дағдыларды бағалауға, ал үміткерлерге білімін растауға көмектесу арқылы кәсіби дамуға және салалық стандарттарға үлес қосады. Компанияның жұмысқа қабылдау бағыты бағалауды ұйымдастыруға және үміткерлердің тәжірибесіне назар аударатын ауқымды халықаралық топты қамтиды.
Software Engineering Manager, AI and Data Platforms
Lead AI fluent engineering and modernize Pearson VUE’s Data Foundations platform. Maintain service continuity while advancing cloud, data, and agentic capabilities for Pearson Virtual Schools.
Сипаттама
- Set team priorities, delivery commitments, and operating practices.
- Assign work, handle escalations, clear blockers, and improve processes.
- Hire engineers and uphold expectations for AI fluent engineering.
- Apply guardrails, human review and fallback, escalation paths, and disclosure for agentic features across relevant product surfaces.
- Require evaluation sets with defined pass criteria and release gates before model backed features reach students.
- Track reliability, hallucinations, model performance, and drift against established thresholds.
- Require specification first development, contract and negative testing, automated merge gates, and model based evaluations.
- Guide contributions to governed shared libraries, MCP servers, evaluation suites, and golden datasets.
- Develop team skills, lead performance and career discussions, and build succession plans.
- Deliver Data Foundations engineering work, including roadmaps, platform readiness, migration sequencing, cutover planning, dependency management, and coordination between source systems and downstream users.
- Set standards for data contracts, quality gates, lineage, observability, access controls, operational readiness, and support ownership.
- Work with Product, Data Engineering, Data Analytics, Solution Architecture, Security, Compliance, DevOps/SRE, and vendor teams.
- Move legacy .NET, ASP.NET WebForms/MVC, AngularJS, jQuery, and SQL Server platforms toward React, TypeScript, modern .NET REST services, containers, AWS, and event driven APIs while maintaining platform continuity.
Талаптар
- At least four years managing engineers who deliver production software, including hiring, performance management, and development.
- An engineering background that supports reviewing technical decisions and earning credibility with AI fluent engineers.
- Experience delivering model backed or agentic features to real users, including pre release evaluation and post release monitoring.
- Experience maintaining quality gates while meeting delivery demands.
- Experience managing legacy and target platforms at the same time.
- Ability to lead a distributed team across time zones with strong written communication practices.
- Experience in regulated or privacy sensitive environments; K-12 and FERPA experience is an advantage.
- A relevant degree or equivalent practical experience.
- Knowledge of artificial intelligence, information security, problem solving, technical judgment, API management, cloud computing, data security, DevOps, software design, AI agents, AutoAI, LLMs, generative AI, evaluation of AI generated content quality, performance management, code review, delivery of AI enabled capabilities, measurement of AI tooling adoption, reusable engineering tools, evaluation suites, data foundations, integration and migration oversight, reliability, observability, and testing.
Артықшылықтар
- Remote work arrangement.
- Full time employment.
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